Responses of quaking aspen (<i>Populus tremuloides</i>) seedlings to solution calcium
Bibliographic record
Abstract
Quaking aspen (Populus tremuloides Michx.) seedlings were grown in nutrient solutions to investigate their responses to a range of solution Ca levels (10-1000 µM) similar to those found in aspen stands of upper Lakes States. Growth increased significantly with increasing level of solution Ca. The level of solution Ca associated with 90% of maximum elongation (critical level) was 61 µM for shoots and 88 µM for roots. Critical Ca levels for biomass probably were lower. Concentrations of Ca in leaves and roots increased significantly with increasing solution Ca. Elongation of shoots and roots was also strongly and positively related to Ca concentrations in leaves and roots. Critical Ca concentrations (oven-dry mass) for shoot elongation were 0.46% in leaf tissue and 0.12% in root tissue, while critical Ca concentrations for root elongation were 0.54% in leaf tissue and 0.13% in root tissue. Solution Ca may have induced deficiencies of other elements, but direct Ca deficiency was the primary cause of growth reduction. These critical Ca levels in solutions or tissues cannot be used to diagnose Ca deficiency in aspen forests until it is known how other soil and plant factors affect the Ca requirement of aspen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".